RVA: 3-D Visualization and Analysis Software to Support Management of Unconventional Oil and Gas Resources

Project Number

DE-FE0005961

Last Reviewed Dated

Wed, 12/02/2015 - 12:00

Goal

This project will produce a state-of-the-art 3-D visualization and analysis software package targeted for improving development of oil and gas resources. The software [RVA (Reservoir Visualization and Analysis)] will display data, models, and reservoir simulation results and have the ability to jointly visualize and query data from geologic models and reservoir simulations to improve exploration and development cycle time and the technical quality of interpretations and development decisions. Key capabilities of RVA will include simultaneous viewing and analysis of multiple reservoir fluids and data mining of combined geologic models and reservoir simulation results.

Performer

University of Illinois/Illinois State Geological Survey, Champaign, IL 61820-7406

Background

Because unconventional oil and gas resources can be distributed in structurally complex or highly compartmentalized reservoirs and in transition or residual oil zones, accurate characterization and efficient management of these resources depend on the ability to view these complex settings and to query them in more sophisticated ways. Advanced reservoir visualization and analysis software can provide significant economic and development advantages to companies that can afford it. Advanced visualization and analysis tools have been useful in providing enhanced solutions to a wide range of technical challenges including quantitative reservoir analysis, migration pathway analysis, integrated reservoir models, interactive well planning, data mining and pattern recognition, and flow simulation analysis for reservoir management and development planning. Economic gains such as cost reduction and cycle time improvement can be realized from the use of advanced visualization in these areas and these tools can be critical for improving the quality of interpretations while providing new insights into the data.

Unfortunately, the costs for purchasing the most sophisticated software can run into the hundreds of thousands of dollars per license. This cost structure makes this technology available to only a subset of the oil and gas industry and out of reach to most researchers and government agencies. In addition, these visualization tools are typically too complicated for infrequent users and this complexity prevents their use in all but the largest firms. More affordable software options do not provide many options. The moderate- to low-cost earth modeling software or stand-alone reservoir simulation packages vary widely in the quality and capabilities of their visualization tools, and can lack the capability to analyze reservoir data or simulation results based on complex queries or filters. Free reservoir simulation packages typically lack any significant visualization capabilities at all and require post-processor software to handle visualization and analysis of data.

There is a clear need for low-cost 3-D visualization software that provides many state-of-the-art capabilities including visualization of multiple fluid phases (e.g., oil, natural gas, water, carbon dioxide (CO2) gas, dissolved concentration of CO2), multiple properties of the various phases (e.g., oil viscosity, pH, alkalinity, pressure, flow lines), and multiple geologic models (e.g., high-resolution anisotropic model, up-scaled model). Advanced data mining capabilities would provide functionality that is unavailable even in the high-end software applications. The value of this functionality is hard to quantify, but based on the recognized value of current state-of-the-art capabilities, advanced data mining will improve the quality of interpretations and overall understanding of reservoir behavior.

Impact

This project will develop a software application [Reservoir Visualization and Analysis (RVA)] that will provide a combination of uncommon and unprecedented capabilities to improve the characterization, analysis, exploration, and development of unconventional oil and gas resources. The features in RVA will directly assist industry, researchers, and government agencies in evaluating the distribution, flow, and character of oil, water, CO2 gas, dissolved CO2, and dissolved solvents associated with various injection and pumping scenarios. RVA will be capable of visualizing the modeled geologic framework and petrophysical properties in sophisticated and sometimes new ways. With its query and data mining tools, RVA will allow users to identify and view locations where CO2 gas is too close to existing non-pumping wells, migrating toward cap rocks or other geologic seals, or where CO2 gas accumulations are expected to leak through geologic seals or cap rocks. Together, these tools will assist in development and management of the resources, increasing production and identifying reservoir fluid or gas movement that could pose a risk to the environment. RVA will be open source, freely-distributed, and will provide capabilities for sophisticated visualization and analysis of unconventional oil and gas resources, CO2sequestration projects, and traditional oil and gas E&P efforts. RVA will be designed around a simple, intuitive interface structure and will provide both uncommon and unprecedented tools to all sectors of the petroleum industry.

Accomplishments (most recent listed first)

Completed an RVA workshop at the University of Texas at Austin. The workshop included support for local users, with a particular emphasis on application of Paraview-RVA for visualization and analysis of UTCHEM simulations.

Contacted Drs. Mojdeh Delshad and Kamy Sepehrnoori from the University of Texas at Austin Department of Petroleum and Geosystems Engineering to set-up a workshop at UT Austin that would support local users, with a particular emphasis on the application of Paraview-RVA for visualization and analysis of UTCHEM simulations. They are very interested in the workshop and at the time of this reporting, they have identified early July as a tentative time frame for the event. The remaining details will be resolved during the next reporting period.

Following consultation with Project Advisory Committee (PAC) members and the Petroleum Technology Transfer Council (PTTC) coordinator at the ISGS, the team has decided to hold a second workshop as a WebEx webinar in an effort to reach the largest number of people who might be interested in using Paraview-RVA for their EOR projects. The second workshop is expected to occur in August, 2015. Any remaining workshop details will be finalized during the next reporting period.

Added code modifications to allow testing of RVA on a wider array of data sets

Debugged UTChem file reading support

Developed new UTChem demonstration simulations

Edited the RVA User Manual

Debugged RVA to support running in Linux

Debugged the 64-bit build of RVA

Completed implementation of Pearson Correlation Coefficients. This measure can now be computed for any pair of values in a reservoir simulation, within a single timestep or across timesteps. This code is present in the CloudRunner code distribution available on GitHub.

Completed a standalone code to compute the fractal spatial statistic of lacunarity across a grid

The latest version of the RVA software has been completed.

The Beta 0.3 version of RVA was made available to the public via the project web site (http://rva.cs.illinois.edu) on January 1, 2013. This release included recently developed visualization code and additions to the code for Focus + Context capabilities, which added flow visualization improvements and spreadsheet visualization functionality to the software. Also added was the capability to read Shapefile format data files (a commonly used GIS data file format) as per the PAC members’ suggestion.

Completed developing the following PAC recommended tools that support calculations of reservoir volumetric and production summations:

Developed a tool to calculate the volume of a given fluid for each cell in the reservoir.

Developed a new filter to calculate the sum of selected parameters for every point or cell in a reservoir model.

Developed a new filter to identify all the cells that connect to a specific point or well and exceed a user-specified defined threshold.

Developed a new filter to identify all of the distinct connected regions in the reservoir that meet user-specified criteria.

Developed a new filter to allow a cross section to be cut through a reservoir model showing only the model results between two user-specified wells.

The Beta 0.2 release of RVA was made available to the public via the project web site (http://rva.cs.illinois.edu) on July 31, 2012.

Don Keefer gave a presentation on the functionality of the Beta 0.1 version of RVA at the meeting of the Illinois Geological Society, a division of the American Association of Petroleum Geologists. The software was well received and the discussion generated several useful considerations for RVA functionality.

Dr. Mojdeh Delshad, University of Texas – Austin, participated with project members in a Skype call to discuss RVA functionality for visualizing and analyzing UTCHEM output files. Dr. Delshad was very happy with the functionality demonstrated, expressed an interest in further collaboration, and agreed to join the PAC.

PAC members met with project team members for a demonstration of the Beta 0.1 RVA functionality. The PAC members in attendance were very satisfied with the progress made in this version and in the subsequent discussion provided a number of worthwhile suggestions for possible feature modifications in future versions of RVA.

The Beta 0.1 release of RVA was made available to the public via the project web site (http://rva.cs.illinois.edu) on January 31, 2012. The Beta 0.1 release was accompanied by a user manual and some demonstration data sets.

The user manual has been started and a version released that was consistent with the Beta 0.1 software release.

A detailed design plan listing all the functions and capabilities of the visualization software has been developed.

Current Status

The Project team completed task related activities on September 15th, 2015. The principal investigator and the project team are working on the project final report.